Browse All Artificial Intelligence Content (807)

Allison announces a public preview feature where GitHub Copilot suggests allowed values while admins define repository custom properties, helping organizations build consistent governance metadata that can be used to scope rulesets across large fleets of repositories.

Sharon Xu announces Foundry Dev Pack, an all-in-one installer that sets up a Microsoft Foundry development environment across the terminal, VS Code, and coding agents, including Azure CLI/azd tooling and starter workflows for creating hosted agents.

Nivas Narayanasamy lays out a practical architecture for making private Azure VMware Solution workloads reachable by Azure AI Foundry agents without moving data. The post shows how to use MCP “bridge” servers on VNet-integrated Azure Container Apps, with ExpressRoute, private endpoints, Entra managed identity, and Key Vault-backed secrets to keep access private and read-only.

Pamela_Fox shares the full set of MCP Live session recordings and resources, covering the Model Context Protocol’s latest spec updates, MCP server/client development in VS Code and GitHub Copilot, enterprise governance with Microsoft Foundry Toolboxes, and evolving MCP authentication patterns.

Aaron Powell shows how to baseline and then raise unit test coverage in the Interview Coach app using Visual Studio’s code coverage tooling and GitHub Copilot’s Test Agent, moving from targeted tests for a single class to solution-wide analysis and test generation.

Justin Yoo walks through a sample “Interview Coach” app that uses the GitHub Copilot SDK as an agent runtime (outside the editor) to run an interview workflow: ingest a resume, ask behavioral/technical questions, store session context, and generate end-of-interview feedback using MCP tools and Agent Framework handoffs.

GitHub shows how to hand off an active GitHub Copilot app session into VS Code so you can keep working in your editor without losing context, including the task plan, conversation history, diffs, and an isolated git worktree, then push changes back to a pull request.

Microsoft Developer shows how to use GitHub Copilot with a Microsoft Foundry skill to review and refactor an existing “Sparkle Cupcakes” agent, aligning it with current Foundry patterns and SDK guidance while improving production readiness.

Satoshi Kubota proposes using a Data Center WordCode Layer (DCWL)—a fixed-length 32-bit word encoding originally aimed at Azure text-processing workloads—to speed up Copilot for Windows and other Windows client text-heavy pipelines such as local RAG, semantic search, and log analysis.

GitHub shares three practical workflow changes to reduce review fatigue and keep pull request backlogs under control when teams adopt AI coding tools, focusing on better prompt inputs, smaller changes via stacked PRs, and shifting reviews toward assessment rather than line-by-line editing.

Wuyi Weng explains how Azure SRE Agent can use an Azure Managed Grafana dashboard (via the MCP endpoint) as executable context to investigate GitHub Copilot telemetry in Application Insights, turning panel queries, variables, and descriptions into fast, accurate triage and per-session diagnoses.

Gaurav Bhardwaj walks through a practical “refund agent” example to show why AI agent observability needs more than green HTTP checks, and how to use Microsoft Foundry plus Azure Monitor (Application Insights and Log Analytics) to trace runs, evaluate tool-call correctness, set alerts, and bake in security and privacy controls.

Mariyaali announces the general availability of the SQL DW operations skill for Microsoft Fabric Data Warehouse, which lets teams use natural-language prompts (for example via GitHub Copilot CLI) to run bounded, read-only diagnostics and get structured findings, evidence, and recommended next steps for common warehouse incidents.

Allison announces new configuration tiers for GitHub Copilot auto model selection—efficiency, balance, and intelligence—so teams can control how Copilot trades off cost, response quality, and response time per prompt, with billing based on the model selected.

John Edward explains Microsoft’s general availability release of MCP-compliant tools in Copilot Studio agent workflows, and why standardized tool access matters for building enterprise AI agents that can reliably interact with proprietary systems, dynamic knowledge sources, and custom actions under existing governance.

This week's Weekly AI Roundup focuses on what it takes to run agents as real production workloads: Azure landing zone-based reference architecture, identity and observability baselines, and cost controls that make audits and FinOps practical. On the grounding side, Fabric and Foundry content reinforced that agent quality depends on a governed meaning layer, with ontology work, lineage graphs, and the growing "IQ" family shaping how truth flows into prompts and tool calls. MCP continued to mature with spec updates, enterprise-focused authentication direction, and more practical implementation patterns, while GitHub Copilot pushed further into agent workflows with managed permissions, reporting, and programmatic security rollouts. We also saw operational AI tighten up in Azure Copilot troubleshooting, faster multilingual speech recognition, and more evidence that closed-loop scientific and security agents need the same governance, evaluation, and lifecycle discipline as any other platfor

kedikala lays out a practical security framework for agentic apps on Azure, focusing on how to keep tool calls safe when untrusted content can steer an agent toward sensitive reads or risky writes. The post breaks controls down across identity, retrieval, request validation, execution constraints, and outcome verification.

GitHub explains how hill climbing can be used to iteratively improve AI agent performance by running targeted evals, benchmarking results, and using the feedback loop to steer responses toward higher accuracy over time.

Allison announces new generally available GitHub Copilot usage metrics that track activity in the dedicated VS Code Agents window, including both aggregate (enterprise/org) and per-user fields for 1-day and 28-day reporting periods.

Allison announces improvements to GitHub Copilot code review, including automatic resolution of addressed review comments, smarter commit message suggestions when applying Copilot fixes, and deeper review analysis using Copilot SDK shell tools plus an ensemble approach for Lite reviews.

Tomoko Tanaka shows how her team turned event marketing runbooks into “ops as code” using GitHub Issues, GitHub Actions, and GitHub Copilot. The post breaks down the repo patterns (issue forms, labels, skills in Markdown, and a DRY_RUN switch) that automate setup, daily screening, and post-event reporting with guardrails.

John Savill shares a quick Azure Weekly Update covering recent platform changes and previews, including VM ephemeral OS disk caching, Azure Functions Flex Consumption custom TLS, user delegation SAS updates, AZD extension framework work, Azure Load Testing Playwright expansion, and new Copilot-related items.

Martin Woodward shares his pick for a new GitHub Copilot feature: the GitHub Copilot app, a native Windows and Mac experience aimed at agentic coding workflows across issues and pull requests, with isolation via separate Git worktrees.

Fokko at Work demos selected new GitHub Copilot features in Visual Studio Code 1.137, including automations, attaching GitHub issues and pull requests directly in chat, and voice mode, with notes on how enterprise policies and pricing plans can affect feature availability.

Visual Studio Code shows how to connect your own Azure-hosted AI models to GitHub Copilot in VS Code using Bring Your Own Key (BYOK), so teams can control which models are available in Copilot and pick the right model for different coding tasks.

Rohon Mohapatra explains how the Citadel reference architecture builds on AI landing zones and Microsoft Foundry to standardize enterprise AI operations—covering shared access controls, observability, identity, and security governance across multiple teams and workloads.

KimVaddi explains why many oil & gas AI initiatives stall on inconsistent business meaning rather than data volume, and argues that the “meaning layer” is the real readiness bottleneck. The post connects OSDU, Azure Data Manager for Energy, and Microsoft Fabric IQ’s preview ontology capability as a practical path to governed, cross-domain reasoning.

Allison summarizes the September 7 weekly GitHub Copilot releases, including Jira integration in the Copilot app, Project HydraFusion model orchestration in Copilot CLI, new agent automations and voice mode updates in VS Code, and expanded enterprise sandbox controls for Copilot in JetBrains.

Kayla Cinnamon explains how to review agent-generated changes inside the GitHub Copilot app using three built-in panels: a diff view for inspecting edits, a terminal for running project commands, and a browser preview for validating UI changes before creating a pull request.

Brendan Burns explains why Microsoft was named a Leader in the 2026 Gartner Magic Quadrant for Container Management, and uses the announcement to outline how AKS, Azure Container Apps, Azure Arc, and Fleet Manager are positioned for AI, hybrid, and edge container operations at scale.

Allison announces a public preview that adds GitHub REST API endpoints for enabling and managing GitHub code scanning’s AI Scan for pull requests at both the organization and repository level, making it easier to roll out AI-powered security detections across selected repos without manual UI configuration.

yaronc announces a preview Fabric REST API that exposes item lineage as a dependency graph you can query from code, enabling automated impact analysis, documentation/catalog scenarios, CI/CD checks, and richer context for AI agents that need to reason about upstream sources and downstream consumers.

Rena Liu announces Azure AI Speech LLM 2607 and explains what changes for developers building speech-to-text and real-time voice experiences, including better multilingual and mixed-language recognition, improved punctuation and numeric transcription, lower latency, and a simpler phrase list parameter for domain-specific customization.

Steven Truitt shares a hands-on walkthrough of using Microsoft Discovery as AI assistance to take a small chip-design project from a rough spec through C and HLS, into Verilog RTL, and finally to physical layout and basic timing/power optimization using open-source EDA tooling.

Microsoft Security Research breaks down a large-scale business email compromise campaign that used AI-assisted executive impersonation and fake invoices to push finance teams into fraudulent ACH payments, and maps practical mitigations using Microsoft Defender for Office 365, Defender XDR, and Security Copilot.

Steve Sweetman explains how to govern AI agent spend in Microsoft Foundry by combining request-path token limits, observability (traces, monitoring, evaluations), and finance-grade budgets, then tying those signals to ROI so teams can decide what to optimize, scale, or retire.

Allison announces the deprecation of the MAI-Code-1-Flash model across GitHub Copilot experiences and points Copilot Enterprise admins to the steps needed to enable the replacement model via Copilot model policies and settings.

Visual Studio Code announces a new “VS Code pet” coding companion that you can trigger from GitHub Copilot Chat in VS Code using the /vscode-pet command, and invites the community to submit name ideas during a one-week window.

Juan Montes profiles Kinaxis’ Maestro platform and how it uses Azure (including AKS, Databricks, Azure OpenAI, Cosmos DB, and Azure AI Content Safety) to run large-scale supply chain scenario modeling, forecasting, and agentic AI experiences. The piece also touches on Kinaxis’ internal use of GitHub Copilot for an agentic, PR-driven development workflow.

Microsoft Developer introduces Toolboxes in Microsoft Foundry as a way to make MCP (Model Context Protocol) integrations more enterprise-ready, with centralized governance, consistent authentication, and reusable configuration across multiple agents and tools.